Related papers: Statistical framework for nuclear parameter uncert…
The s-process in massive stars, producing nuclei up to $A\approx 90$, has a different behaviour at low metallicity if stellar rotation is significant. This enhanced s-process is distinct from the s-process in massive stars around solar…
We study the dependence of primordial nuclear abundances on fundamental nuclear observables such as binding energies, scattering lengths, neutron lifetime, \textit{etc.} by varying these quantities. The numerical computations were performed…
The abundances of n-capture elements in the CEMP-r/s stars agree with predictions of intermediate n-density nucleosynthesis, at $N_\mathrm{n}\sim 10^{13}$-$10^{15} \mathrm{cm}^{-3}$, in rapidly-accreting white dwarfs (RAWDs). We have…
We propose using the frequency-domain bootstrap (FDB) to estimate errors of modeling parameters when the modeling error is itself a major source of uncertainty. Unlike the usual bootstrap or the simple $\chi^2$ analysis, the FDB can take…
Probabilistic prediction of sequences from images and other high-dimensional data is a key challenge, particularly in risk-sensitive applications. In these settings, it is often desirable to quantify the uncertainty associated with the…
Context: Recent reaction rate evaluations include reaction rate uncertainties that have been determined in a statistically meaningful manner. Furthermore, reaction rate probability density distributions have been determined and published in…
In this paper, we present an analytical study of the relationship between the statistical distribution of a physical parameter and the uncertainties in the physical quantities used to determine it through indirect measurement. We…
There is increasing interest in using high-energy collisions to probe the structure of nuclei, in particular with the high-precision data made possible by collisions performed with pairs of isobaric species. A systematic study requires a…
The prompt neutron period (the negative reciprocal of the prompt neutron decay constant) can be estimated using the Rossi-alpha technique that is predicated on fitting Rossi-alpha histograms and of interest in nuclear criticality safety and…
Cosmological observations from Big Bang Nucleosynthesis and the Cosmic Microwave Background (CMB) offer crucial insights into the Early Universe, enabling us to trace its evolution back to lifetimes as short as 0.01 seconds. Upcoming CMB…
I discuss the recent progress in our understanding of nucleosynthesis via rapid neutron capture, the r-process, based on meteoritic data for the early solar system and observations of stars at low metallicities. At present, all data require…
It is proposed here to investigate three major properties of the nuclear force that influence the amplitude of shell gaps, the nuclear binding energies as well as the nuclear $\beta$-decay properties far from stability, that are all key…
A method is proposed to compute robust inner-approximations to the backward reachable set for uncertain nonlinear systems. It also produces a robust control law that drives trajectories starting in these sets to the target set. The method…
In this work, a method is proposed for combining differential and integral benchmark experimental data within a Bayesian framework for nuclear data adjustments and multi-level uncertainty propagation using the Total Monte Carlo method.…
Nuclear reaction rates are a fundamental yet uncertain ingredient in stellar evolution models. The astrophysical S-factor pertaining to the initial reaction in the proton-proton chain is uncertain at the 1% level, which contributes a…
Markov Chain Monte Carlo (MCMC) methods have become a cornerstone of many modern scientific analyses by providing a straightforward approach to numerically estimate uncertainties in the parameters of a model using a sequence of random…
We consider the problem of parameterizing Newman-type models of Li-ion batteries focusing on quantifying the inherent uncertainty of this process and its dependence on the discharge rate. In order to rule out genuine experimental error and…
Neutron noise analysis is a predominant technique for fissile matter identification with passive methods. Quantifying the uncertainties associated with the estimated nuclear parameters is crucial for decision-making. A conservative…
Efficient treatment of systematic uncertainties that depend on a large number of nuisance parameters is a persistent difficulty in particle physics experiments. Where low-level effects are not amenable to simple parameterization or…
Survival models are used in various fields, such as the development of cancer treatment protocols. Although many statistical and machine learning models have been proposed to achieve accurate survival predictions, little attention has been…